Instructions to use harish/PT-v3-dev-test-all-PreTrain-e7-select with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-v3-dev-test-all-PreTrain-e7-select with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="harish/PT-v3-dev-test-all-PreTrain-e7-select")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e7-select") model = AutoModelForMaskedLM.from_pretrained("harish/PT-v3-dev-test-all-PreTrain-e7-select") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a16599bc5c094c3ea2549a0a4bd8cf429eea3359b0c34c92bbfdc58bc963a05a
- Size of remote file:
- 712 MB
- SHA256:
- a8a8b18ab09614a1658a3c54dd7918aa9d309c4390874c526556aa049cb9caf9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.